中国地理科学 ›› 2018, Vol. 28 ›› Issue (6): 957-972.doi: 10.1007/s11769-018-1005-z

• 论文 • 上一篇    下一篇

Soil and Vegetation Spectral Coupling Difference (SVSCD) for Minerals Extraction from Hyperion Data in Vegetation Covered Area

CHEN Shengbo1, HUANG Shuang1, LIU Yanli1, ZHOU Chao1,2   

  1. 1. College of Geoexploration Science and Technology, Jilin University, Changchun 130026, China;
    2. National Marine Environmental Monitoring Center, Dalian 116023, China
  • 收稿日期:2018-05-07 修回日期:2018-09-02 出版日期:2018-12-27 发布日期:2018-11-01
  • 通讯作者: CHEN Shengbo.E-mail:chensb0408@126.com E-mail:chensb0408@126.com
  • 基金资助:

    Under the auspices of National Science and Technology Major Project of China (No. 04-Y20A35-9001-15/17), the Program for JLU Science and Technology Innovative Research Team (No. JLUSTIRT, 2017TD-26), the Changbai Mountain Scholars Program, Jilin Province, China

Soil and Vegetation Spectral Coupling Difference (SVSCD) for Minerals Extraction from Hyperion Data in Vegetation Covered Area

CHEN Shengbo1, HUANG Shuang1, LIU Yanli1, ZHOU Chao1,2   

  1. 1. College of Geoexploration Science and Technology, Jilin University, Changchun 130026, China;
    2. National Marine Environmental Monitoring Center, Dalian 116023, China
  • Received:2018-05-07 Revised:2018-09-02 Online:2018-12-27 Published:2018-11-01
  • Contact: CHEN Shengbo.E-mail:chensb0408@126.com E-mail:chensb0408@126.com
  • Supported by:

    Under the auspices of National Science and Technology Major Project of China (No. 04-Y20A35-9001-15/17), the Program for JLU Science and Technology Innovative Research Team (No. JLUSTIRT, 2017TD-26), the Changbai Mountain Scholars Program, Jilin Province, China

摘要:

Remote sensing data have been widely applied to extract minerals in geologic exploration, however, in areas covered by vegetation, extracted mineral information has mostly been small targets bearing little information. In this paper, we present a new method for mineral extraction aimed at solving the difficulty of mineral identification in vegetation covered areas. The method selected six sets of spectral difference coupling between soil and plant (SVSCD). These sets have the same vegetation spectra reflectance and a maximum different reflectance of soil and mineral spectra from Hyperion image based on spectral reflectance characteristics of measured spectra. The central wavelengths of the six, selected band pairs were 2314 and 701 nm, 1699 and 721 nm, 1336 and 742 nm, 2203 and 681 nm, 2183 and 671 nm, and 2072 and 548 nm. Each data set's reflectance was used to calculate the difference value. After band difference calculation, vegetation information was suppressed and mineral abnormal information was enhanced compared to the scatter plot of original band. Six spectral difference couplings, after vegetation inhibition, were arranged in a new data set that requires two components that have the largest eigenvalue difference from principal component analysis (PCA). The spatial geometric structure features of PC1 and PC2 was used to identify altered minerals by spectral feature fitting (SFF). The collecting rocks from the 10 points that were selected in the concentration of mineral extraction were analyzed under a high-resolution microscope to identify metal minerals and nonmetallic minerals. Results indicated that the extracted minerals were well matched with the verified samples, especially with the sample 2, 4, 5 and 8. It demonstrated that the method can effectively detect altered minerals in vegetation covered area in Hyperion image.

关键词: spectral difference coupling, vegetation covered area, Hyperion image, mineral extraction

Abstract:

Remote sensing data have been widely applied to extract minerals in geologic exploration, however, in areas covered by vegetation, extracted mineral information has mostly been small targets bearing little information. In this paper, we present a new method for mineral extraction aimed at solving the difficulty of mineral identification in vegetation covered areas. The method selected six sets of spectral difference coupling between soil and plant (SVSCD). These sets have the same vegetation spectra reflectance and a maximum different reflectance of soil and mineral spectra from Hyperion image based on spectral reflectance characteristics of measured spectra. The central wavelengths of the six, selected band pairs were 2314 and 701 nm, 1699 and 721 nm, 1336 and 742 nm, 2203 and 681 nm, 2183 and 671 nm, and 2072 and 548 nm. Each data set's reflectance was used to calculate the difference value. After band difference calculation, vegetation information was suppressed and mineral abnormal information was enhanced compared to the scatter plot of original band. Six spectral difference couplings, after vegetation inhibition, were arranged in a new data set that requires two components that have the largest eigenvalue difference from principal component analysis (PCA). The spatial geometric structure features of PC1 and PC2 was used to identify altered minerals by spectral feature fitting (SFF). The collecting rocks from the 10 points that were selected in the concentration of mineral extraction were analyzed under a high-resolution microscope to identify metal minerals and nonmetallic minerals. Results indicated that the extracted minerals were well matched with the verified samples, especially with the sample 2, 4, 5 and 8. It demonstrated that the method can effectively detect altered minerals in vegetation covered area in Hyperion image.

Key words: spectral difference coupling, vegetation covered area, Hyperion image, mineral extraction